SISTEM DETEKSI GANGGUAN USUS BESAR (COLON) DENGAN CITRA IRIS MENGGUNAKAN CIRCULAR HOUGH TRANSFORM DAN BACKPROPAGATION BERDASARKAN IRIDOLOGI
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Institusion
Universitas Sriwijaya
Author
FATHAN MUSTAGHFIRIN (STUDENT ID : 09011281320021)
Erwin Erwin (LECTURER ID : 0029017101)
Erwin Erwin (LECTURER ID : 0029017101)
Subject
TJ1180 Machining, Ceramic materials--Machining-Strength of materials-Machine tools-Design and construction
Datestamp
2019-10-02 04:58:27
Abstract :
The iris consists of complex body tissues that can be seen directly without medical devices. The nerves in the iris are connected to every organ and body network through the brain and nervous system. Thus, it is possible to detect health problems using iris as an indicator, this method known as iridology. Iridology allows the classification of colon disorders using the iris patterns they have. The characteristics that are considered as indicators in iridology, including patterns of characteristics such as the eyes are almost normal, ballooning, and spasm which indicates the presence of a large intestinal disorder experienced by the patient. In the process of identifying iris patterns, there is a lot of noises such as eyelashes, light reflection, and pupils within the iris images, so an image segmentation method that can separate the noises from the iris is needed, therefore Circular Hough Transformation which can be used to segment the image of iris. After the iris image is segmented, the method for the classification process is needed to group iris images based on the characteristic traits of the disease. In conducting this classification, the author used the Backpropagation method. The program is created using Netbeans IDE 8.2 software in the Java. The test results using confusion matrix for each image class, showed an average precision of 73.3%, recall 57.9%, and accuracy of 73.3%.
The iris consists of complex body tissues that can be seen directly without medical devices. The nerves in the iris are connected to every organ and body network through the brain and nervous system. Thus, it is possible to detect health problems using iris as an indicator, this method known as iridology. Iridology allows the classification of colon disorders using the iris patterns they have. The characteristics that are considered as indicators in iridology, including patterns of characteristics such as the eyes are almost normal, ballooning, and spasm which indicates the presence of a large intestinal disorder experienced by the patient. In the process of identifying iris patterns, there is a lot of noises such as eyelashes, light reflection, and pupils within the iris images, so an image segmentation method that can separate the noises from the iris is needed, therefore Circular Hough Transformation which can be used to segment the image of iris. After the iris image is segmented, the method for the classification process is needed to group iris images based on the characteristic traits of the disease. In conducting this classification, the author used the Backpropagation method. The program is created using Netbeans IDE 8.2 software in the Java. The test results using confusion matrix for each image class, showed an average precision of 73.3%, recall 57.9%, and accuracy of 73.3%.
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